It is widely believed that complex dynamical systems possess considerably more predictability than is apparent by a naive mathematical or statistical analysis. For instance, it is known that simple mathematical recursions can lead to extraordinary complex behavior leading to time series that pass many tests for being random.
There are many situations in nature when there are patterns (correlations) present, a well as randomness. The eye is a sensory organ particularly well adapted to recognize such structure in complex patterns in the presence of noise. By processing data to uncover underlying patterns, and then displaying the processed data, the observers may then see patterns which lead to a more precise fundamental description of the data, and ultimately aid in understanding the underlying dynamical system and the physiology.
Methods of generating and displaying time series data have been disclosed. The present invention is an improvement of a method disclosed by D. Ruelle, Proceedings of the Santa Barbara Conference on Non-Linear Dynamics, Aug. 1987.